Automated store technologies

ABSTRACT

Apparatuses and methods provide an automated store with a number of product locations and a fetch and delivery bucket that conveys product from a shelf location to a delivery location. Cameras and sensors within the automated store acquire data that may be stored in a remote database and analyzed to improve the reliability of the delivery process. Camera images may also be used to re-position the fetch and delivery bucket in real time, to provide images of actual, available product to consumers via a remote interface, to determine inventory, and to monitor the activities of replenishers and service personnel, and to generally operate the automated store remotely.

CROSS-REFERENCE TO RELATED CASES

The present application is a Continuation of International PatentApplication No. PCT/US2019/048927, filed on Aug. 29, 2019, which claimspriority to U.S. Provisional Patent Application No. 62/724,465, entitled“AUTOMATED STORE TECHNOLOGIES,” filed on Aug. 29, 2018, whichapplications are incorporated herein by reference. To the extentappropriate, a claim of priority is made to each of the above disclosedapplications.

TECHNICAL FIELD

The present subject matter relates to the field of vending machines andmore particularly to automated stores.

BACKGROUND

More recently vending machines have become more sophisticated and arebeing used to sell higher value products such as electronics, cosmetics,and other higher value consumer items. In retail applications it hasbeen desirable to have a design of a machine that displays the productsavailable for sale to consumers. The most popular recent designs allowproducts to be assorted on shelves in merchandise displays akin toretail shelves. In such designs, consumers can see the productsavailable to be dispensed and can select them via a user interface forimmediate delivery. Still, these designs are typically stand-alone unitsthat must be physically visited by a consumer to make a purchase. Andthese designs must be visually inspected to determine whether they needto be replenished and whether they need to be serviced. The need forsuch visits by both the consumer and service personnel is inefficient—aconsumer might not wish to purchase the products that are available inthe vending machine and service personal would prefer to visit thevending machine only when it actually needs service or replenishing.

It is therefore desirable to have an automated store that is equipped tobe remotely monitored and operated, both by remote staff and bycustomers.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments are illustrated by way of example and not limitation inthe figures of the accompanying drawings, in which like referencesindicate similar elements, and in which:

FIG. 1 is a perspective view of an embodiment of an automated store;

FIG. 2 is an expanded view of an embodiment of a cabinet subassembly foran automated store;

FIG. 3 is a perspective view of an embodiment of a subassembly for anautomated store;

FIG. 4 is a perspective view of an embodiment of a fetch and deliverybucket for an automated store;

FIG. 5 is a photograph of an internal section of an automated store froma camera on an embodiment of a fetch and delivery bucket for anautomated store and an associated screenshot from an embodiment of asystem for remotely managing an automated store;

FIG. 6A is a photograph depicting the placement of a camera on anembodiment of an automated store;

FIG. 6B is a photograph further depicting the placement of a camera onan automated store of FIG. 6A;

FIG. 6C is front view depicting the placement of a camera on anembodiment of an automated store;

FIG. 7 is a photograph of an internal section of an automated store froma camera on an embodiment of an automated store and an associatedscreenshot from an embodiment of a system for remotely managing anautomated store;

FIG. 8A is a perspective view of an embodiment of an automated store;

FIG. 8B is a perspective view of a detail of the embodiment of anautomated store of FIG. 8A;

FIG. 8C is a perspective view of a detail of the embodiment of anautomated store of FIG. 8A;

FIG. 9 depicts a screenshot from an embodiment of a system for remotelymanaging an automated store;

FIG. 10 depicts a screenshot from an embodiment of a system for remotelymanaging an automated store;

FIG. 11 depicts a screenshot from an embodiment of a system for remotelymanaging an automated store;

FIG. 12 depicts a screenshot from a user interface of a system forremotely managing an automated store;

FIG. 13A is a perspective view of an embodiment of an automated store;

FIG. 13B is a perspective view of a detail of the embodiment of anautomated store of FIG. 13A;

FIGS. 14A, 14B and 14C are individual sections of a single screenshotfrom an embodiment of a system for monitoring automated store trafficand user behavior;

FIGS. 15A, 15B and 15C are individual sections of a screenshot from anembodiment of a system for monitoring automated store traffic and userbehavior;

FIGS. 16A, 16B and 16C are individual sections of a screenshot from anembodiment of a system for monitoring automated store traffic and userbehavior;

FIG. 17A is a perspective view of an embodiment of an automated store;

FIG. 17B is a perspective view of the embodiment of an automated storeof FIG. 17A;

FIG. 18A is a perspective view of an embodiment of an automated store;

FIG. 18B is a perspective view of the embodiment of an automated storeof FIG. 18A;

FIG. 19 is a simplified, exemplary block diagram of an embodiment of asystem for controlling a dispenser of shelved products; and

FIG. 20 is an exemplary block diagram of a computing device from thesystem of FIG. 19.

DETAILED DESCRIPTION

FIG. 1 is a perspective view depicting an embodiment of an automatedstore 100 (also known as a “vending machine”). In FIG. 1, automatedstore 100 includes an intelligent door 125 and dispensers 105 of shelvedproducts (not shown) on shelves 107. Intelligent door 125 furtherincludes a dispensing door 110, a user interface 115, a controller 120,and a display 130. Display 130 may display information regarding theavailable products. User interface 115 allows a user to choose and payfor products. Controller 120 may receive input from the user interface115 and various sensors in the vending machine and controls the varioussystems of the vending machine. Products are stored on shelves 107 withdifferent products on the same shelf being separated by a dispenser 105.Products are fed into a fetch and delivery bucket 302 (FIG. 3) whenbucket 302 is moved into position under instruction from controller 120and engages gears at the end of dispenser 105 that cause an extension ondispenser 105 to move forward, in turn causing product to be advanced bythe extension until the product is pushed onto a platform of fetch anddelivery bucket 302. Bucket 302 is then moved to position behinddispensing door 110, delivering product to dispensing door 110. A usermay access delivered products when dispensing door 110 is opened oninstruction from controller 120. In an embodiment, controller 120 mayalso be connected to a network allowing controller 120 to be accessedvia a network interface such as an application executed by a mobilecommunications device or a website accessed by a personal computer. Inan embodiment, display 130 may also be used by the consumer to chooseand pay for products.

FIG. 2 is an expanded view of an embodiment of a cabinet subassembly 200for automated store 100. In FIG. 2, cabinet subassembly 200 may includea tubular frame 202 to which intelligent door 125, product door 212,side panels 204, 206, a top panel 208, a bottom panel 210, a clearproduct door 212 and a back panel 214 (or back panels 214 a, 214 b) areattached to define an interior space. The interior space may be accessedby opening one or both of intelligent door 125 and product door 212,which may be attached by hinges to frame 202.

FIG. 3 is a perspective view of an embodiment of a subassembly ofinternal parts 300 for automated store 100. In FIG. 3, internal parts300 includes fetch and delivery bucket 302 (or simply “bucket”), an X-Ypositioning system 304, a peripheral box 306, and shelving end supports308, 310, 312. X-Y positioning system 304 includes a Y-rail 314, anX-rail 316, an X-positioner mechanism 318, and a Y-positioner mechanism606 (FIG. 6). X-Y positioning system 304 is connected to bucket 302 and,on instructions from controller 120, moves bucket 302 along X-rail 316and Y-rail 314 to position bucket 302 at product locations, where bucket302 is able to engage a dispenser 105 and cause dispenser 105 to move aproduct onto a platform of bucket 302. Once product is loaded intobucket 302, X-Y positioning system 304 then moves bucket 302 to an areabehind dispensing door 110. In an embodiment, peripheral box 306 mayhouse a personal computer (PC), which may be controller 120, a modem orother network connection, internal switches (e.g., for controlling X-Ypositioning system 304, bucket 302, and dispensing door 110, andelectronic locks), and power supplies.

FIG. 4 is a perspective view of an embodiment of fetch and deliverybucket 302 for automated store 100. In FIG. 4, bucket 302 is shownprimarily from the point of view of a product on a shelf. Bucket 302 mayinclude an inwardly-facing camera 402, an outwardly-facing camera 410, aflap 406, a bucket door 414, and infrared (IR) sensor 408, and radiofrequency identification (RFID) scanner 412. Inwardly-facing camera 402captures a field of view 404 that includes much or all of the interiorof bucket 302, including flap 406, and also including product(s),dispenser(s), and shelves. Outwardly-facing camera 410 captures a fieldof view that includes much or all of flap 406, bucket door 414, and,when bucket door is opened, dispensing door 110, and when dispensingdoor 110 is opened, the area in front of dispensing door 110. Flap 406has a lowered position in which it is a platform for receiving productfrom a dispenser 105 and a raised position causing product to slideforward toward the dispensing side of bucket 302. Flap 406 may be movedbetween the two positions by DC motors on instruction from controller120. Bucket door 414 in the vertical position shown helps retain productwithin bucket 302. When bucket 302 is positioned in the dispensing areaand both bucket door 414 and dispensing door 110 are opened, a customermay remove product from bucket 302. IR sensor 408 may be interfaced withcontroller 120 and used to determine the presence of product withinbucket 302. RFID scanner 412 may be interfaced with controller 120 andused to determine both the presence and identity of product withinbucket 302. In embodiments, the images from cameras 402, 410 may bestill images, video images, or both.

Thus, in the embodiment of FIG. 4, images from camera 402 may beanalyzed to determine the position of bucket 302, and elements of bucket302, with respect to a particular dispenser 105 and a particular productat that dispenser. In an embodiment, the images may be analyzed bycontroller 120 in real-time to determine whether bucket 302 is properlyaligned with a dispenser 105, or shelf 107, or product. In response tocontroller 120 determining that bucket 302 is improperly aligned,controller 120 may instruct X-Y positioning system 302 to makeadjustments to correct the mis-alignment of bucket 302.

In an embodiment, camera 402 may record and store images from multipletransfers of product from a particular dispenser 105 (such transfers maybe considered a “dispense” or a “dispense cycle”). The images may bestored on a database accessible via a network. The stored images may bestored such that images related to failures of the transfer areidentified and made available so that Artificial Intelligence (AI)methods, such as machine learning, may be applied to the stored imagesto develop instructions for improving the transfer of product. Forexample, the AI methods may review the transfers from a particulardispenser or all dispensers to the flap 406 (or platform) of bucket 302.In an embodiment, the developed instructions (from a particulardispenser, or a number of dispensers) are applied by controller 120 whencontrolling the transfer from the particular dispenser 105. In anembodiment, the developed instructions are applied by controller 120when controlling the transfer from the particular dispenser 105 of aparticular product. In an embodiment, the instructions developed for aparticular dispenser may be applied by controller 120 to control thetransfer from a different dispenser. In an embodiment, the instructiondeveloped regard a particular product instead of a particular dispenserand the developed instructions are applied by controller 120 whencontrolling the transfer of the particular product, regardless of thedispenser. Thus, generally, AI methods may be used to developinstructions for improving the transfer of one or more differentproducts from one or more dispensers onto the platform of bucket 302.

Similarly to camera 402, the images from camera 410 may be analyzed todetermine the position of bucket 302, and elements of bucket 302, withrespect to a particular dispensing door 110. In an embodiment, theimages may be analyzed by controller 120 to determine whether bucket 302is properly aligned with a dispensing door 110.

In an embodiment, camera 410 may record and store images from multipletransfers of products from bucket 302 through dispensing door 110. Theimages may be stored on a database accessible via a network. ArtificialIntelligence (AI) methods, such as machine learning, may be applied tothe stored images to develop instructions for improving the transfer ofproducts from bucket 302 through dispensing door 110. In an embodiment,the developed instructions are applied by controller 120 whencontrolling the transfer from bucket 302. In an embodiment, thedeveloped instructions are applied by controller 120 when controllingthe transfer of a particular product. In an embodiment, the instructionsdeveloped for a particular product may be applied by controller 120 tocontrol the transfer of a different product. Thus, generally, AI methodsmay be used to develop instructions for improving the transfer of one ormore different products from bucket 302 through dispensing door 110.

In an embodiment, the images stored by camera 402, camera 410, or both,may be consulted by remote staff regarding a particular transfer of aproduct to a particular customer. The remote staff may consult theimages to, e.g., determine or verify that the customer received aproduct, or that the customer received the proper product.

In an embodiment, bucket door 414 opens by rotating forward from itsbase, draw-bridge style, through an open dispensing door 110. With theforward rotation of bucket door 414, flap 406 rotates further up untilit is or approaches the vertical, which accomplishes two goals: first,product is urged forward and made more accessible by the customer, andsecond, flap 406 is positioned vertically, which prevents access intothe interior of the automated store, hindering the unauthorized removalof products.

In an embodiment, RFID scanner 412 may determine the identity of aproduct on the shelf position nearest bucket 302. Thus, in theembodiment, RFID scanner 412 may be used to confirm the identity of theproduct before it is loaded onto bucket 302.

FIG. 5 illustrates a screenshot 500 from an embodiment of a system forremotely managing automated store 100 and an associated image 502 of aninternal section of automated store 100 from camera 402 on fetch anddelivery bucket 302. In FIG. 5, screenshot 500 is from a monitoringprogram, which may include a networked user interface accessible from,e.g., a website or from an application executing on a device, such as amobile communications device, with access to controller 120 through anetwork (e.g., network 1935 (FIG. 19)). The user interface allows remotestaff, for example, to perform the listed operations remotely. In FIG.5, the listed operations are shown grouped according to types: payment,network, and firebase. The listed operations are exemplary and are notexhaustive. In FIG. 5, the user has selected “Bucket Image,” which opensa window with an image 502 from inwardly-facing camera 402. Image 502shows two shelves 107, part of the back face of bucket 302 and a section504 of the interior of bucket 302. Image 502 shows that the upper shelf107 contains products and that the lower shelf 107 is empty (the detailsto the left side of lower shelf 107 depict a dispenser and apparatusassociated with the dispenser). Section 504 of the interior of bucket302 may include flap 406. Thus, using the system and networked userinterface, remote staff may perform operations such as retrieving a“bucket image,” which allows inspecting the interior of remote store 100using camera 402.

FIG. 6A, FIG. 6B, and FIG. 6C illustrate the placement of an interiorcamera 602 within an embodiment of automated store 100. In FIG. 6A,camera 602 is attached within automated store 100 at the comer of theintersection of top panel 208 and side panel 204. Camera 602 is shownwith wiring linking it to networked controller 120 and a networkeddatabase. Thus, images taken by camera 602 may be stored in the externaldatabase, as with images from cameras 402 and 410. Camera 602 issituated in front of shelving end support 308 and between shelving endsupport 308 and product door 212 (not shown). FIG. 6B illustrates thatthe placement of camera 602 between shelves 107 and product 212 (notshown) allows camera 602 to capture a field of view that includes thefront faces of shelves 107. In FIG. 6C, camera 602 is shown to capture afield of view 604 that ranges from the far upper right corner and nearlower left comer of automated store 100. FIG. 6C further illustratesthat X-Y positioner system 304 includes a Y-positioner mechanism 606that positions bucket 302 vertically on Y-rail 314. Controller 120instmcts both X-positioner mechanism 318 and Y-positioner mechanism 606to position bucket 302.

In the embodiment, the field of view provided by camera 602 allowsimages to be taken of the movement and loading of bucket 302. Suchimages may be analyzed, like images from cameras 402 and 410, bycontroller 120 to direct the proper positioning of bucket 302. Suchimages may also be analyzed, like images from cameras 402 and 410, by AImethods to develop instructions for controller 120 that improve thetransfer of product from shelves 107 into bucket 302, or from bucket 302through dispensing door 110. In an embodiment, images from the threecameras 402, 410, and 602 may be collectively analyzed by AI methods todevelop instructions for controller 120 that improve the transfer ofproduct from shelves 107 into bucket 302, or from bucket 302 throughdispensing door 110.

In an embodiment, automated store 100 may intelligently track whichproducts cause which errors during a dispense cycle and also which vendpositions work better for vending those products. Automated store 100may collect data from its cameras and other sensor and using, e.g.,machine learning or other AI methods, get smarter about vending productsover time without any human interaction.

In an embodiment, one or more of cameras 402, 410, and 602 may bewirelessly networked with controller 120 and the networked database.

FIG. 7 is a photograph of an internal section of automated store 100from a camera on an embodiment of automated store 100 and an associatedscreenshot from an embodiment of a system for remotely managingautomated store 100;

FIG. 7 illustrates a screenshot 700 from an embodiment of a system forremotely managing automated store 100 and an associated image 702 of aninternal section of automated store 100 from interior camera 602 withinan embodiment of automated store 100. In FIG. 7, screenshot 700 is fromthe monitoring program described with regard to FIG. 5. In FIG. 7, theuser has selected “Interior Image,” which opens a window with an image702 from interior camera 602. Image 702 illustrates shelves filled withproduct (the dispensers are omitted). Image 702 also illustrates bucket302 between the shelves and front panel 212, and positioned behinddispensing door 110. Thus, using the system and networked userinterface, remote staff may perform operations such as retrievingan“interior image,” which allows inspecting the interior of remote store100 using camera 402. In embodiments, the images from camera 602 may bestill images, video images, or both. In an embodiment, the images storedby camera 602 may be consulted by remote staff regarding a particulartransfer of a product to a particular customer. The remote staff mayconsult the images to, e.g., determine or verify that the customerreceived a product, or that the customer received the proper product. Inan embodiment, camera 602 may be instructed to obtain images during theprovisioning or other service of automated store 100. These images maythen be consulted by remote staff to, e.g., determine or verify thatautomated store 100 was properly provisioned.

FIG. 8A is a perspective view of an embodiment of automated store 100.Intelligent door 125 pivots open upon hinges attaching it to the cornerof automated store 100. Front panel 212 pivots open upon hingesattaching it to the opposing front corner of automated store 100. InFIG. 8a upper section 802 and lower section 804 of intelligent door 125have been rendered partially transparent to show aspects of the innerapparatus. FIG. 8B further illustrates details of section 802 and FIG.8C further illustrates details of section 804. In FIG. 8B, an electroniclock 806 engages automated store 100, retaining both intelligent door125 and front panel 212 in the closed position. Similarly, in FIG. 8C,an electronic lock 808 engages automated store 100, retaining bothintelligent door 125 and front panel 212 in the closed position.Electronic locks 806, 808 may be networked such that they are incommunication with controller 125 and may be actuated via the monitoringprogram.

FIG. 9 illustrates a screenshot 900 from an embodiment of a system forremotely managing automated store 100. In FIG. 9, screenshot 900 is fromthe monitoring program described with regard to FIG. 5. Screenshot 900illustrates that remote staff may choose to monitor automated stores atvarious locations, e.g., South Station Bus Terminal 902, and LGA-TermB-Conc A 904.

FIG. 10 illustrates a screenshot 1000 from an embodiment of a system forremotely managing automated store 100. In FIG. 10, screenshot 1000 isfrom the monitoring program described with regard to FIG. 5. Screenshot1000 illustrates that remote staff may choose from a number of availablecommands 1002, which are segregated by types, including: generalcommands 1004 and robot commands 1006, where general commands 1004include commands 1008 and robot commands include commands 1010.

FIG. 11 illustrates a screenshot 1100 from an embodiment of a system forremotely managing automated store 100. In FIG. 11, screenshot 1100 isfrom the monitoring program described with regard to FIG. 5. Screenshot1100 illustrates a payment command group 1102, a network command group1104, and a firebase command group 1106.

FIG. 10 illustrates a screenshot 1000 from an embodiment of a system forremotely managing automated store 100. In FIG. 10, screenshot 1000 isfrom the monitoring program described with regard to FIG. 5. Screenshot1000 illustrates that remote staff may

FIG. 12 illustrates a screenshot 1200 from an embodiment of a system forremotely managing automated store 100 and an associated image 1204 ofdisplay screen 130. FIG. 12 illustrates that remote staff may select ageneral command 1104 called a “UI screenshot” 1202 to view display 130in real time, where “UI screenshot” refers to an embodiment in whichdisplay 130 is a user interface. Thus, remote staff may be able toreview a customer interaction with the automated store. The embodimentallows remote staff to determine whether display 130 is providinginformation that corresponds accurately to the products contained withinthe automated store (and verified, e.g., using cameras 402, 410, or602).

FIG. 13A is a perspective view of an embodiment of an automated store100 incorporating a traffic monitoring camera 1302. In FIG. 13A, trafficmonitoring camera 1302 is located on the front of automated store 100 inintelligent door 125 above display 130. Traffic monitoring camera 1302captures a field of view that includes a customer interacting withautomated store 100 and potential customers (“foot traffic”) passing infront of automated store 100.

FIG. 13B is a perspective view of the embodiment of FIG. 13A with thesection about camera 1302 on intelligent door 125 rendered partiallytransparent to reveal further details of the location and orientation ofcamera 1302.

FIGS. 14A-14C illustrate a single screenshot 1400 from an embodiment ofa system for remotely managing automated store 100. In FIG. 14A-14C,screenshot 1400 is from the monitoring program described with regard toFIG. 5. Screenshot 1400 illustrates that traffic monitoring camera 1302may obtain and store images in the remote database. The images may beanalyzed and processed by remote staff. The images may be analyzed andprocessed using AI methods, such as machine learning. The analysis maydevelop data regarding the customers and potential customers who pass byas foot traffic, such as average dwell time and conversion ratio. Suchdata may be displayed on the dashboard of screenshot 1400.

FIGS. 15A-15C illustrate a single screenshot 1500 from an embodiment ofa system for remotely managing automated store 100. In FIG. 15A-15C,screenshot 1500 is from the monitoring program described with regard toFIG. 5. Screenshot 1500 further illustrates that traffic monitoringcamera 1302 may obtain images that may be processed and analyzed toprovide information regarding customers and potential customers ofautomated store 100. In FIG. 15, an upper chart shows watchers andconversion ratio as a function of date, and a lower chart shows dwelltime, attention time, and attraction ration as a function of date.

FIGS. 16A-16F illustrate a single screenshot 1600 from an embodiment ofa system for remotely managing automated store 100. In FIG. 16A-16F,screenshot 1600 is from the monitoring program described with regard toFIG. 5. Screenshot 1600 further illustrates how traffic images may beprocessed and analyzed to provide information regarding customers andpotential customers of automated store 100.

FIG. 17A and FIG. 17B; and FIG. 18A and FIG. 18B depict furtherembodiments of automated stores. FIG. 17 and FIG. 18 illustratedprimarily glass versions of an automated store. Primarily glass versionsof automated stores get away from the look and feel of a typicalautomated store and move toward the look and feel of a retail showcase.The automated stores illustrated in FIG. 17 and FIG. 18 include a framebut no sheet metal on the front and very little on the sides. In theembodiments, wiring may be incorporated into the glass, or wirelesscommunication may be used to minimize wiring and enhance a minimalistlook and feel.

FIG. 17A and FIG. 17B are perspective views of an embodiment of anautomated store 1700. Automated store 1700 is visually different fromautomated store 100 described above, but should be understood to includethe internal parts of automated store 100 and function as described withregard to automated store 100. For that reason, automated store 1700will be minimally described to reduce unnecessary duplication. In FIGS.17A and 17B, automated store 1700 includes a transparent front panel1702 and a transparent side panel 1704. Transparent front panel 1702further includes a dispensing door 1708, a user interface 1710, adisplay screen 1712, and a controller (not shown). Automated store 1700further includes shelves 1706, a Y-rail 1714, and dispensers 1716.

FIG. 18A and FIG. 18B are perspective views of an embodiment of anautomated store 1800. As with automated store 1700, automated store 1800is visually different from automated store 100 described above, butshould be understood to include the internal parts of automated store100 and function as described with regard to automated store 100. Forthat reason, automated store 1800 will be minimally described to reduceunnecessary duplication. In FIGS. 18A and 18B, automated store 1800includes a transparent front panel 1802 and transparent side panels 1804and 1805. Transparent front panel 1802 further includes a dispensingdoor 1808, a user interface 1810, a display screen 1812, and acontroller (not shown). Automated store 1800 further includes shelves1806, a Y-rail 1814, and dispensers 1816.

Regarding the embodiment of FIGS. 1-8C, camera 402 on fetch and deliverybucket 302 provides for the recording and transmitting of a video imageof the dispense cycle to a remote database. The video image may beviewed by remote monitoring staff. Such videos may include videos offailed dispense cycles. The videos of the dispense cycles, successful aswell as failed, may be identified and incorporated into a referencelibrary of dispense cycles. Using A methods, such as machine learning,the videos (failed dispense cycles, successful dispense cycles, or both)may be analyzed to so that the automated store may become moreintelligent and reliable over time. For example, the AI analysis maydetermine procedural or structural changes intended to reduce faileddispense cycles. In addition, in the embodiment, the cameras can seewhat is happening in real time and provide this information to thecontroller, which may then instruct the X-Y positioning system how toadjust during a dispense cycle. For example, during a“fetch” phase of adispense cycle, the controller may instruct the motors of the X-Ypositioning system to adjust up or down, left or right, and in microsteps to ensure accuracy. Furthermore, during a dispense cycle, thecontroller may adjust the dispenser motor speed, the timing of when thefetch system returns to the home position, and the position of the flapthat holds the product in the bucket as the bucket is moved to the“home”delivery position behind the dispensing door. In the embodiment, one ormore IR sensors 408 in the bucket may detect when a product is placed inthe bucket. The embodiment may include a camera, e.g., camera 410, witha field of view that captures a product being delivered into thedelivery bin behind the dispensing door (e.g., dispensing door 110). Thecamera on the bucket or a camera on the delivery bin can transmit animage of the product in the bin real time (optical image recognition) toinput into the dispense cycle logic. In embodiments with cameras orsensors that may identify products, the product recognition can verifythat the consumer gets the correct product they ordered and not anincorrect one, which may occur if, e.g., a replenisher placed a productin the wrong location. Such product recognition is especially importantfor applications such as prescription drugs. In an embodiment, the fetchand delivery bucket may also dump products into a hold/recycle binrather than deliver the product directly to an end customer through thedispensing door.

Regarding FIGS. 1-8C, camera 402 on bucket 302 may also be used toverify the actual existence of a specific product on the shelf andtransmit the image to a remote database such as a database that would beaccessible through a website or accessible by a mobile applicationexecuting on a mobile device. Such an application or website, forexample, may provide for remote shopping for products in an automatedstore. In an embodiment, remotely-purchased products may be held by theautomated store until the arrival of the end consumer or a deliveryperson. Camera 402 may transmit and image to the remote consumer of theactual, physical product on the shelf. Because the product is being heldin a secure system, the system controller logic can ensure the productis not released until certain conditions are met, e.g., verification ofthe consumer identity through input of a code into the user interface115, or face recognition via an image acquired from external camera1302. A mobile app or website may provide the consumer with an image ofthe actual, available product and a message to the effect of, e.g.,“Here it is, do you want to come and collect it or do you want it sentto you? Delivery method A will take X minutes and cost X$ or deliverymethod B will take Y minutes and cost Y$.”

Still regarding FIGS. 1-8C, camera 402 on bucket 302 may also be used tocreate images or a video of the inventory in the machine by controller120 positioning bucket 302 at each product location and instructingcamera 402 to create and transmit an image or video. The images maybetransmitted to a remote database for viewing by an auditor who desires,e.g., visual evidence of the inventory to verify advice from areplenisher, or to confirm a service personnel's actions. If areplenisher is stealing products it will become obvious from the imageanalysis (camera 602 may also be used to create such images ofreplenisher or service personnel activities). The system (e.g.,controller 120, a website, or a mobile application) may be programmedsuch that an image of inventory is recorded automatically immediatelyafter a replenisher locks the door and returns the system to operationalmode.

As discussed, camera 602, mounted in the upper left front comer of theautomated store system, may also provide images. The intelligence fromcombining images or videos from camera 402 in the XY bucket with imagesfrom camera 602 may be improved over the intelligence from either cameraalone. For example, to check on a replenisher's honesty, if there ismissing inventory remote staff may analyze the static camera 602 videorecording of what the replenisher actually did while at the machine.That information may be compared to or cross-referenced againstinventory transaction data, whether entered from touch screen (e.g.,display 130), scanner or other source such as the images of theinventory from camera 402 on bucket 302.

Thus, in an embodiment of a method, the apparatus of FIGS. 1-8C may beremotely monitored using images acquired from one or more of the camerasby: acquiring and storing images of the automated store inventory beforea replenishment; receiving information showing products purportedlyadded to the automated store inventory; acquiring and storing images ofthe automated store inventory after the replenishment; and comparing thestored images before and after the replenishment to determine whetherthe products purportedly added to the automated store inventory were infact added to the automated store inventory. In an embodiment, RFIDscanners at each product location may collect data regarding productadditions and the timing and be used to confirm whether thereplenishment was performed as before to determine whether thereplenishment as directed. In an embodiment, the identify of areplenisher may be confirmed by providing each replenisher with areplenisher-specific code for the electronic locks. In the embodiment,the code used to access an automated store during a replenishment isassociated with data (e.g., images, IR, and RFID data) associated withthe replenishment so that issues found from analysis of thereplenishment data may be associated with the appropriate replenisher.

In an embodiment, the combination of data from multiple cameras alongwith data from sensors either in the delivery bucket or on the shelvesmay provide intelligence that may be used to improve dispense cyclereliability. Static camera 602 may optically see the product removedfrom the shelf to the bucket, and identify which product was moved.Camera 402 in bucket 302 may verify the transfer from shelf to deliverysystem, and identify the product from close-up. And shelf sensors, suchas infrasonic, capacitive, magnetic, optical (IR sensor 408) or RFIDsensor 410 may detect transfer off the shelf. The exact quantity of eachproduct may depend on the sensor system.

In an embodiment, the sensors (e.g., cameras and other sensors) trackthe bucket vending position and collect data (e.g., images and RFIDs)that provide information allowing the controller, application, orwebsite, to check inventory levels. In addition, data from these sensorsenables the system to create a virtual planogram (a physical merchandiselayout) of the products within the automated store. Personnel, e.g., atechnician, may then copy the planogram from a computer or a piece ofpaper to physically make the changes. The system may then check thetechnician's work by checking whether the layout matches the expectedvirtual layout, and this removes errors from the system. For example,the technician may compare the virtual planogram against the actualautomated store layout, note where the virtual planogram is inaccurate,make corrections to the virtual planogram, and input the correctionsonto the virtual planogram. The system may, using AI methods, review thechanges against the data used to make the virtual planogram anddetermine how to improve the creation of the virtual planogram so thatit is more accurate. In an embodiment, personnel could create variousplanograms to see what works with the automated store, e.g., physicallylay out the planograms to see what “works,” then scan the planogram intothe system, which then virtually duplicates layout (or layouts) aspotential planograms. In an embodiment, the sensors in the bucket (e.g.,camera 402) may be used for visual recognition of the product on theshelf in a physical layout to tell the virtual system the exact producton the shelf. For example, the system may take camera images combinedwith data of the bucket location to determine the product actually ateach individual product shelf location. The determined product may beinput into the virtual planogram to correct or verify the product in thevirtual planogram. Similar, in an embodiment, the system, using dataobtained from the various sensors, may determine the identity of thereplenished product (not just the inventory levels) to verify that theproduct is the correct product for that shelf position. In anembodiment, the inventory levels of the system are known virtually(e.g., using the virtual planogram). When a replenishment order israised (i.e., currently 5 in stock, ship 10 more), a replenisher doesthe physical work to stock the shelf. As stated, the system knows it has5 of the particular product. With the raising of the replenishmentorder, the system receives a communication telling the system to expect10 more. When the replenisher loads the new stock, the inventory counter(e.g., the system using the sensors to detect product and data of thebucket location to develop an inventory) can then check the positionsand check the inventory levels to have a complete closed loop inventorycount of all items in the system. Such a closed-loop inventory countremoves errors in inventory and drastically speed up the replenishmentprocess by removing the need for manual inventory counts. In anembodiment, the sensors may collect data that the system interprets anddetermines that an item may not have been dispensed properly. The systemmay then try to automatically resolve the improper dispensing by usingthe conveyor bucket to dispense the product back onto the shelf, or intoa waste area. Such an automatic resolution of an improper dispense cycleeliminates the need for a technician to visit the automated store toremove a jam or dispense failure.

Regarding FIGS. 5-12, in an embodiment, automated store 100 may beremotely managed by software that incorporates workflows that may befollowed by skilled or even relatively unskilled personnel with nospecific automated store experience to complete a task addressed by theworkflow. Remote electronic locks 806, 808 may be incorporated in theautomated store to ensure the security of the product and to provide anaudit trail regarding who has had access to the interior of theautomated store and when. The automated locks may be unlocked withsoftware codes. Such remote control of the automated locks facilitatesthe efficient central management of the automated store, increasessecurity, and optimizes efficient utilization and dispatch of authorizedpersonnel. The remote software system may include and maintain adatabase of available resources, such as contact information fortechnical staff to maintain the system when something breaks, or forreplenishers who may receive inventory and replenish the automatedstore.

The automated software may include an automated ticketing and alertsystem for maintenance of automated stores in which algorithms analyzedata streams being transmitted in real time from the store network from,e.g., store cameras and sensors. When certain events or sets of data aresuch that an algorithm determines that an alert condition exists, thenan alert may be raised automatically by the software system executing,e.g., on controller 120. Alerts may be categorized into two types:dispatch alerts and research alerts. A dispatch alert automaticallyopens a ticket in the ticketing system and transmits the ticket to theappropriate service provider for that machine. The alert received by theservice provider includes details of the alert, the automated storemachine, and the location details. Included with the alert is data thatis extracted from a database to advise the services what parts,supplies, and tools are required to fix the alert. Such information maybe transmitted via email, SMS or other electronic form to a PC orhandheld device such as a mobile communications device. The alert mayalso be transmitted to the automated store so that, when the replenisherarrives and identifies themselves through the automated storeauthentication process, the process looks up and verifies the servicescredentials in real time. Once the replenisher or service personnel islogged in the alert appears on the service screen of the automatedstore. Included with the alert (on the automated store display as wellas on the mobile communications device or PC that the alert was alsosent to) is workflow information that lists the steps for resolving thealert, and may also track the services being performed by thereplenisher or service personnel through the steps. Such workflowinstructions may include text, images, video instructions, or voicenarrative, or a combination of these. In embodiments, the system mayalso offer click-to-connect live to call center or NMS technical staffto allow real time video or text assistance. Where the call is directedmay depend on where the service person is in the workflow process (i.e.,call center at start of process, but NMS later in the workflow ifadvanced technical support is required).

When an alert is raised a time stamp may be recorded in the database. Atime stamp may also be recorded when the service person acknowledges thealert, which allow the responsiveness (SLA compliance) of that serviceperson to be tracked. The automated store sensors and cameras can beused to help verify and record information that can be fed into theworkflow process. For example, the standard time for a service can berecorded by a timestamp automatically generated when the servicerauthenticates at the automated store. A timestamp may be generated whenthe doors are unlocked. And a timestamp may be generated when the systemis returned to operational mode. The automated store controller cantransmit information such as information regarding dispense test cyclesand what was done by a servicer. The internal camera can acquire a videorecording of servicer activity that may be stored in the databaseagainst the alert such that NMS staff can retrieve and review the videoagainst the alert.

Thus, in an embodiment the automated store may automatically detectfailures and initiate repair by: acquiring data regarding the automatedstore from at least one of a camera, an IF sensor, or an RFID sensor;storing the data in a database; analyzing by the controller or otheranalysis software; the stored data; determining from the data analysisthat a failure or alert condition exists; and sending, by the controllera message to a service provider regarding the determined failure oralert condition.

In an embodiment there are workflow systems for replenishment of theautomated store stores. In the embodiment, the replenishment orders areautomatically generated through the automated software, which mayinclude a supply chain management software module. When replenishmentorders are shipped out of a distribution center (DC) the contents of theshipment are transmitted to the automated store. When the replenisherloads the shelves the replenisher advises the system of the number ofitems of each product. If the logical count varies, the automated storereplenishment screen (e.g., display 130) asks the servicer to reviewwithout telling them the correct answer. In an embodiment, the inventorycount may be transmitted automatically by reading sensors, e.g., RFIDsensors at each product location. The cameras in the automated store canbe used to create an inventory count, and can also be used to record thereplenishment process in video file that is stored in the databaseagainst the replenishment, and can also be used to create and store avisual of the inventory display before and after replenishment (foraudit purposes). The workflow instructions can guide an untrainedreplenisher through the restocking process.

Thus, in an embodiment of a method, the apparatus of FIGS. 1-8C may beremotely inventoried using images acquired from one or more of thecameras or using data from RFID sensors, or data from both cameras andRFID sensors by: the controller receiving data regarding a dispensedproduct; the controller identifying the dispensed product from thereceived data; and the controller deducting the dispensed product froman inventory of products in the automated store. In embodiments, thedata regarding the dispensed product may be received from at least oneof: a camera within the automated store, an RFID scanner at a productshelf location, an RFID scanner on the fetch and delivery bucket. In anembodiment, the dispensed product may be deducted from an initialinventory that was performed by: the controller positioning a camera ateach product shelf location; the camera acquiring images at each productshelf location and storing the images in a database accessible by thecontroller; the controller analyzing the stored images to determine theinventory of the automated store. In an embodiment, the dispensedproduct may be deducted from an initial inventory that was performed by:RFID sensors at each product shelf location acquiring data of productsplaced at the shelf locations during a replenishing; the RFID sensorsstoring the acquired data in a database accessible by the controller;the controller analyzing the stored data to determine the inventory ofthe automated store. In an embodiment, the inventory of the automatedstore may be monitored in real time by the controller determining arunning inventory after performing an initial inventory, with thedispensed products being determined using data from at least one ofcamera images and RFID sensors. In the embodiment, as the controllerdetermines that the remaining number of any particular product dropsbelow a threshold value, the controller may send a re-order request to areplenisher for that particular product to be replenished.

In an embodiment, the automated store electronic lock also allowscentral issuance of authentication information to allow services to beactivated and deactivated remotely. When combined with the automatedstore workflow system this improves flexibility and increases SLAresponse times and reduces reliance on individuals.

In an embodiment, machine learning software can analyze videos ofservice routines that are performed to learn best practices and toincorporate into AI systems where the machine learns how toself-correct. For example, service routines that are performed inminimal time may be recorded and identified as exemplary forincorporation and analysis by the AI system. Remote staff using camerasmay remotely operate the automated store machines, and such operationscould be automated by machine learning systems over time.

Regarding 13A-16F, in an embodiment, an automated store may include atraffic monitoring and user behavior monitoring system. Camera 1302provides images that may be analyzed to provide data for the monitoringsystem. In the embodiment, the traffic and user behavior monitoringsystem may, e.g., count traffic, may measure how many people stop towatch, may measure user session length, may measure user engagements toshop at the machine, and may measure conversions to sales transactions.The system may also analyze camera data to measure demographics ofwatchers. Such demographic data can be combined with transactional data,such as products purchased. The data may be transmitted (preferablywithout identifying people personally) to remote databases and beavailable for viewing in a dashboard by location or by groups oflocations or by products sold from groups of locations. In theembodiment, when a watcher or potential consumer is detected the systemmay also collect dwell time and emotion and other data about theconsumer. The demographic data may be combined with media servingcapability at an automated store—where ads may be cued based ondemographic or ethnicity, emotion or other data determined by the systembased on the images from the monitoring camera/software. Embodiments ofthe automated store system incorporate the monitoring capability withthe ability to serve demographic-specific offers both on the storepromotional display screen 130 and on the user interface (shoppingtransaction screen) on the website or mobile application. In anembodiment, the automated store may learn about its consumers andpersonalized transactions and subsequently make targeted offers topotential customers as part of its consumer experience, and withoutconsumers being identified personally. In an embodiment, the monitoringand user behavior system may also combine anonymous information withaccount information where users have opted in and agree to be recognizedpersonally.

In an embodiment, an automated store allows printing of individualproduct labels before dispensing. Some applications, such as thedispensing of prescription drugs, require labels to be fixed to theproduct as part of the process. If drugs are prepackaged in appropriatequantities then an automated store can be used to automate thedispensing of drugs. In an embodiment, a printer (thermal or inkjet) ismounted on the front of bucket 302 and the product packaging is designedto allow custom printing on the front facing of the package. In theembodiment, bucket 302 moves to the product location on the shelf.Bucket 302 then holds the product in place by engaging a dispenser anddriving a pusher at the back of the row of products to move the packagesforward until the first product is flush with the front edge of theshelf and against the printer. The appropriate information may then beprinted on the package.

In an embodiment, an automated store automatically recognizes members orloyal customers and personalizes their transaction. An outward facingcamera of an automated store and software that references a customerimage library in, e.g., the remote database, in real time provides forfacial recognition of a returning customer. The returning customer maybe a returning customer of a specific type/brand of automated store, areturning customer from any brand of automated store in the network, ora returning customer from any automated store in the network.

In an embodiment, an automated store may provide a mobile applicationwhere the exact (or functionally similar) consumer experience on a touchscreen of an automated store is offered on a mobile phone so thatconsumers can shop and pay from their phone without having to touch themachine or go to the machine. The application may transmit near-fieldcommunication (NFC) or quick response (QR) codes to a customer's phone(or on the automated store), which the customer may present to a cameraat the automated store to collect purchases.

FIG. 19 is a simplified, exemplary block diagram of an embodiment of asystem 1900 for implementing the embodiments of systems and methodsdisclosed herein. System 1900 may include a number of input devices suchas, e.g., a camera 1905 (e.g., cameras 402, 410, and 602), a sensor 1910(e.g., IR sensor 408, RFID scanner 412), a user interface 1920 (e.g.,user interface 115), an interactive display 1935 (e.g., display 130).Sensors 1905, 1910, 1920, and 1925 are in communication with a computingdevice 1915 (e.g., controller 120, or the PC within peripheral box 306).Computing device 1915 may further be in control of, e.g., bucket 302,cameras 402, 410, 602, X-Y positioning system 304, and dispensing door110. Computing device 1915 may receive input from interface 115 anddisplay 130, and display information on interface 115 and display 130.Sensors 1905, 1910, 1920, and 1925 may supply data to computing device1915 via communication links 1930 or other network 1935.

Computing device 1915 may include a user interface (e.g., interface 115)and software, which may implement the steps of the methods disclosedwithin. Computing device 1915 may receive data from sensors 1905, 1910,1920, and 1925, via communication links 1930, 1935, which may behardwire links, optical links, satellite or other wirelesscommunications links, wave propagation links, or any other mechanismsfor communication of information. Various communication protocols may beused to facilitate communication between the various components shown inFIG. 19. Distributed system 1900 in FIG. 19 is merely illustrative of anembodiment and does not limit the scope of the systems and methods asrecited in the claims. In an embodiment, the elements of system 1900 areincorporated into an automated store (e.g., automated store 100). One ofordinary skill in the art would recognize other variations,modifications, and alternatives. For example, more than one computingdevice 1915 may be employed. As another example, devices 1905, 1910,1920, and 1925 may be coupled to computing device 1915 via acommunication network (not shown) or via some other server system.

Computing device 1915 may be responsible for receiving data from devices1905, 1910, 1920, and 1925, performing processing required to implementthe steps of the methods, and for interfacing with the user. In someembodiments, computing device 1915 may receive processed data fromdevices 1905, 1910, 1920, and 1925. In some embodiments, the processingrequired is performed by computing device 1915. In such embodiments,computing device 1915 runs an application for receiving user data,performing the steps of the method, and interacting with the user. Inother embodiments, computing device 1915 may be in communication with aserver (e.g., via network 1935), which performs the required processing,with computing device 1915 being an intermediary in communicationsbetween the user and the processing server.

System 1900 may enable users to access and query information developedby the disclosed methods. Some example computing devices 1915 includedevices running the Apple iOS®, Android® OS, Google Chrome® OS, SymbianOS®, Windows Mobile® OS, Windows Phone, BlackBerry® OS, Embedded Linux,Tizen, Sailfish, webOS, Palm OS® or Palm Web OS®.

FIG. 20 is an exemplary block diagram of a computing device 1915 fromthe system of FIG. 19. In an embodiment, a user interfaces with thesystem through computing device 1915 (e.g., though user interface 115,display 130, and network 2035), which also receives data and performsthe computational steps of the embodiments. Computing device 1915 mayinclude a display, screen, or monitor 2005, housing 2010, input device2015, sensors 2050, and a security application 2045. Housing 2010 housesfamiliar computer components, some of which are not shown, such as aprocessor 2020, memory 2025, battery 2030, speaker, transceiver, antenna2035, microphone, ports, jacks, connectors, camera, input/output (I/O)controller, display adapter, network interface, mass storage devices2040, and the like. In an embodiment, sensors 2050 may include sensors1905, 1910, 1920, and 1925 in communication with computing device 1915

Input device 2015 may also include a touchscreen (e.g., resistive,surface acoustic wave, capacitive sensing, infrared, optical imaging,dispersive signal, or acoustic pulse recognition), keyboard (e.g.,electronic keyboard or physical keyboard), buttons, switches, stylus, orcombinations of these.

Display 2005 may include dedicated LEDs for providing directing signalsand feedback to a user.

Mass storage devices 2040 may include flash and other nonvolatilesolid-state storage or solid-state drive (SSD), such as a flash drive,flash memory, or USB flash drive. Other examples of mass storage includemass disk drives, floppy disks, magnetic disks, optical disks, magnetooptical disks, fixed disks, hard disks, CD-ROMs, recordable CDs, DVDs,recordable DVDs (e.g., DVD-R, DVD+R, DVD-RW, DVD+RW, HD-DVD, or Blu-rayDisc), battery-backed-up volatile memory, tape storage, reader, andother similar media, and combinations of these.

System 2000 may also be used with computer systems having configurationsthat are different from computing device 1915, e.g., with additional orfewer subsystems. For example, a computer system could include more thanone processor (i.e., a multiprocessor system, which may permit parallelprocessing of information) or a system may include a cache memory. Thecomputing device 1915 shown in FIG. 20 is but an example of a computersystem suitable for use. For example, in a specific implementation,computing device 1915 is mounted to an automated store and incommunication with the sensors, devices, and positioning systems of thevending machine. Other configurations of subsystems suitable for usewill be readily apparent to one of ordinary skill in the art.

The following paragraphs include enumerated embodiments.

1. An automated store comprising: a plurality of product locations; aplatform within the automated store and movable between a plurality offirst platform positions and a second platform position adjacent to adispensing area, each first platform position being adjacent to aproduct location; a security door with a first door position and asecond door position, the security door hindering access to the platformthrough the dispensing area when in the first door position and nothindering access to the platform when in the second door position; afirst camera connected to the platform, the first camera capturing afirst field of view including at least part of the platform and at leastpart of an adjacent product location when the platform is at a firstplatform position; a positioning system connected to the platform suchthat the platform is movable by the positioning system between each ofthe plurality of product locations and the dispensing area; a controllerincluding a processor and memory, the memory including instructions, thecontroller communicably connected to the first camera and thepositioning system; and a network connector for connecting the firstcamera and controller to a database through a network. In an embodiment,a plurality of automated stores may be located within the same locationor adjacent to each other within the same location.

2. The automated store of embodiment 1 further comprising a secondcamera connected to the platform and communicably connected to thecontroller and network connector and capturing a second field of view,wherein, when the platform is at the second platform position and thesecurity door is in the second door position, the second field of viewincludes at least part of the platform and at least part of thedispensing area.

3. The automated store of embodiment 1 further comprising a third cameraconnected to the platform and communicably connected to the controllerand network connector and capturing a third field of view including aninterior area of the automated store between the plurality of productlocations and a front panel.

4. The automated store of embodiment 1, wherein the platform includes aflap movable from a first flap position to a second flap position, thesecond flap position inclined such that when the platform is in thesecond flap position, the flap slants downward in a direction toward thedispensing door.

5. The automated store of embodiment 1 further comprising a userinterface and an electronic lock communicably connected to the networkconnector, the electronic lock controllable using the user interface andthrough a network.

6. The automated store of embodiment 1, further comprising a sensorassociated with the platform, the sensor one of: an infrasonic sensor, acapacitive sensor, an infrared sensor, a magnetic sensor, or an opticalsensor. In an embodiment a sensor associated with a platform may includeone of: an infrasonic sensor, a capacitive sensor, an optical sensor, aninfrared sensor, optical sensor or other type of usable sensor.

7. The automated store of embodiment 1, further comprising a sensorassociated with each of the plurality of product locations, the sensorone of: an infrasonic sensor, a capacitive sensor, an infrared sensor, amagnetic sensor, or an optical sensor. In an embodiment a sensorassociated with each of the product locations may include one of: aninfrasonic sensor, a capacitive sensor, an optical sensor, an infraredsensor, optical sensor or other type of usable sensor.

8. A method comprising: providing an automated store comprising: aplurality of product locations; a platform within the automated storeand movable between a plurality of first platform positions and a secondplatform position adjacent to a dispensing area, each first platformposition being adjacent to a product location; a security door with afirst door position and a second door position, the security doorhindering access to the platform through the dispensing area when in thefirst door position and not hindering access to the platform when in thesecond door position; a first camera connected to the platform, thefirst camera capturing a first field of view including at least part ofthe platform and at least part of an adjacent product location when theplatform is at a first platform position; a positioning system connectedto the platform such that the platform is movable by the positioningsystem between each of the plurality of product locations and thedispensing area; a controller including a processor and memory, thememory including instructions, the controller in communication with thefirst camera and the positioning system; and a network connectionconnecting the first camera and controller to a database through anetwork; acquiring, by the controller, first images from the firstcamera; and storing, by the controller, the acquired first images in thedatabase.

9. The method of embodiment 8, wherein the first images are acquiredwhen the platform is at the first platform position adjacent to theproduct location, the method further comprising: analyzing, by thecontroller, the acquired first images to develop data representing theposition of the platform with respect to the product location; anddirecting, by the controller using the developed data, the positioningsystem to move the platform with respect to the shelf position.

10. The method of claim 8, wherein the acquired first images includeimages of a product, the method further comprising: analyzing theacquired first images to identify a product dispensed to a customer. Themethod in claim 10 wherein the acquired first images include images of aproduct, the method further comprising: analyzing the acquired firstimages to identify multiple selected products dispensed to a customerduring the same event—(Multy-Vend). The method of claim 10, wherein theacquired first images are analyzed by an administrator to identify theproduct dispensed to a customer. The method of claim 10 wherein theplatform camera is used to verify customer has removed product fromcustomer delivery area

11. The method of claim 10, wherein the acquired first images areanalyzed by an administrator to identify the product dispensed to acustomer.

12. The method of claim 10, wherein the acquired first images areanalyzed by an image recognition module executing on a server toidentify the product dispensed to a customer. The method of claim 12wherein the acquired first images are of customer removal of productfrom a customer delivery area.

13. The method of claim 8, wherein the acquired first images includeimages of a product, the images being accessible by a mobileapplication. The method of claim 13 wherein the acquired first imagesare of customer removal of product from a customer delivery area.

14. The method of claim 8, wherein the acquired first images includeimages of a plurality of transfers of product from the product locationto the platform, the images being analyzed to develop instructions forimproving the transfer of product from the product location to theplatform, the method further comprising: receiving, by the controller,the developed instructions; and adjusting, by the controller using thedeveloped instructions, a transfer of product from the product locationto the platform.

15. The method of claim 14, wherein the adjusting the transfer ofproduct includes at least one of: adjusting, by the controller, a speedof transfer of product from the product location to the platform; oradjusting, by the controller, a position of the platform during thetransfer of product from the product location to the platform.

16. The method of claim 8, wherein the provided automated store furthercomprises a second camera connected to the platform and in communicationwith the controller and network connection and including a second fieldof view, wherein, when the platform is at the second platform positionand the security door is in the second door position, the second fieldof view includes at least part of the platform and at least part of thedispensing area, the method further comprising: acquiring, by thecontroller, second images from the second camera; and storing, by thecontroller, the acquired second images in the database.

17. The method of claim 16, wherein the second images are acquired whenthe platform is at the second platform position adjacent to thedispensing area, the method further comprising: analyzing, by thecontroller, the acquired second images to develop data representing theposition of the platform with respect to the dispensing area; anddirecting, by the controller using the developed data, the positioningsystem to move the platform with respect to the dispensing area.

18. The method of claim 16, wherein the acquired second images includeimages of a product, the method further comprising: analyzing theacquired second images to identify a product dispensed to a customer.

19. The method of claim 18, wherein the acquired second images areanalyzed by an administrator to identify the product dispensed to acustomer.

20. The method of claim 18, wherein the acquired second images areanalyzed by an image recognition module executing on a server toidentify the product dispensed to a customer.

21. The method of claim 16, wherein the acquired second images includeimages of a product, the images being accessible by a mobileapplication.

22. The method of claim 16, wherein the acquired first images includeimages of a plurality of transfers of product from the platform to thedispensing area, the images being analyzed to develop instructions forimproving the transfer of product from the platform to the dispensingarea, the method further comprising: receiving, by the controller, thedeveloped instructions; and adjusting, by the controller using thedeveloped instructions, a transfer of product from the platform to thedispensing area.

23. The method of claim 22, wherein the adjusting the transfer ofproduct includes at least one of: adjusting, by the controller, a speedof transfer of product from the platform to the dispensing area; oradjusting, by the controller, a position of the platform during thetransfer of product from the platform to the dispensing area.

In the description above and throughout, numerous specific details areset forth in order to provide a thorough understanding of an embodimentof this disclosure. It will be evident, however, to one of ordinaryskill in the art, that an embodiment may be practiced without thesespecific details. In other instances, well-known structures and devicesare shown in block diagram form to facilitate explanation. Thedescription of the preferred embodiments is not intended to limit thescope of the claims appended hereto. Further, in the methods disclosedherein, various steps are disclosed illustrating some of the functionsof an embodiment. These steps are merely examples, and are not meant tobe limiting in any way. Other steps and functions may be contemplatedwithout departing from this disclosure or the scope of an embodiment.

1-20. (canceled)
 21. An automated store, comprising: a processor; and amemory coupled to the processor and storing instructions that, whenexecuted by the processor perform operations, comprising: controllingmovement of platform between a first platform position adjacent to aproduct location and a second platform position adjacent to a dispensingarea; causing movement of a security door from a first position, inwhich access to the platform is hindered, to a second position in whichaccess to the platform is not hindered; and causing an image sensor tocapture an image that includes at least part of the platform and atleast part of a product location.
 22. The automated store of claim 21,further comprising instructions for moving a flap associated with theplatform from a first flap position to a second flap position.
 23. Theautomated store of claim 22, wherein the second flap position causes theflap to be inclined such that the flap slants downward in a directiontoward the dispensing area.
 24. The automated store of claim 21, furthercomprising instructions for causing a display of a user interface on adisplay of the automated store.
 25. The automated store of claim 1,further comprising instructions for receiving sensor information thatidentifies an item in the dispensing area.
 26. The automated store ofclaim 21, further comprising instructions for receiving sensorinformation that identifies an item associated with the productlocation.
 27. The automated store of claim 21, further comprisinginstructions for receiving sensor information that identifies a currentposition of the platform as the platform moves between the firstplatform position and the second platform position.
 28. A method,comprising: causing movement of a platform within an automated storebetween a first platform position and a second platform position, thefirst platform position being adjacent to a product location and thesecond platform position being adjacent to a dispensing area; causingmovement of a security door from a first door position to a second doorposition to provide access to the platform via the dispensing area; andcausing an image capture device coupled to the platform to capture animage that includes at least part of the platform and at least part ofthe product location when the platform is at the first platformposition.
 29. The method of claim 28, further comprising analyzing theimage to determine a position of the platform with respect to theproduct location.
 30. The method of claim 29, further comprisingadjusting a position of the platform based, at least in part, on thedetermined position of the platform with respect to the productlocation.
 31. The method of claim 30, further comprising storing theadjusted position of the platform.
 32. The method of claim 31, furthercomprising using the adjusted position of the platform as the firstplatform position.
 33. The method of claim 28, wherein the imageincludes information about an item located at the product location. 34.The method of claim 33, further comprising analyzing the image toidentify the item.
 35. The method of claim 28, further comprisingcausing the image capture device to capture another image that includesat least part of the platform and at least part of the dispensing areawhen the platform is at the second platform position.
 36. The method ofclaim 35, further comprising analyzing the another image to determine aposition of the platform with respect to the dispensing area.
 37. Themethod of claim 36, further comprising adjusting a position of theplatform based, at least in part, on the determined position of theplatform with respect to the dispensing area.
 38. The method of claim37, further comprising storing the adjusted position of the platform.39. The method of claim 38, further comprising using the adjustedposition of the platform as the second platform position.
 40. Anautomated store, comprising: a product location; a platform movablebetween a first platform position associated with the product locationand a second platform position adjacent to a dispensing area. a securitydoor having a first door position that hinders access to the platformwhen the platform is not at the second position and allows access to theplatform when the platform is at the second position; and an imagecapture device for capturing an image that includes at least part of theplatform and at least part of the product location when the platform isat the first platform position.